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Hi everyone, I am wondering if someone can help explain the difference between Node/Edge and View/Connection Properties. I am extremely confused on these concpts as I read through the CDF data modelling tutorial.My current perspective is that Node/Edge and the knowledge graph defined by Nodes and Edges is the most “vanilla” version. Where as a Data Model made up of Views and Connection Properties is a similar construct but based on a specific perspective. The analogy between a View and Node in a relational DB sense will be a table and a view.Is my understanding correct? If so, I am wondering what is the actual need of Node/Edge given there is already Containers that perform the data storage like a SQL table would do? It seems to me that View, Connection Properties and Data Models are sufficient enough to produce any type of sementic model?
Hi, my name is Justin Kracht and I’m a Data Science Analyst at Accenture in Oslo, Norway. I’m very new to Cognite and am taking this course to learn more about the platform and hopefully be able to apply that knowledge on future projects. I’m excited to get started!Justin
Hi Cognite Community,I am Raunak Agarwal. I work as a Consulting Project Manager for AsInt (www.asint.net). Basically, I am a Mechanical Engineer by trade and working with global customers and Asset Intensive clients in Asset Management, Reliability and Mechanical Integrity space.I am having total 10+ years of varied experience from Downstream O&G Petrochemicals Sector to Information Management, Digital & Sustainability. I’m just starting the course “Cognite Data Fusion Architecture and Implementation Fundamentals”.Glad to connect with you all in this community.Thanks & Regards,Raunak AgarwalMy LinkedIn coordinates - LinkedIn. Lets collaborate and learn together.
Greetings Cognite Community!It is my pleasure to introduce myself as Vishnu Iyengar, an undergraduate student at Rutgers University, pursuing a degree in Industrial and Systems Engineering. I am excited to be a part of the Cognite community and eager to learn more about Cognite CDF. As a research assistant at our University’s Energy Lab, I recognize the importance of keeping up with the latest technologies and Cognite CDF is at the forefront of innovation. I have been impressed by the warm welcome and openness of the Cognite community thus far. My career aspirations are focused on the Data Science field and I believe that Cognite CDF can provide me with the knowledge and experience to achieve my goals. I am grateful to be a part of such a welcoming and supportive community. Thank you all for this opportunity and I look forward to learning and growing with all of you!
We're excited to introduce the InRobot course on Cognite Academy.InRobot empowers industrial companies to harness the power of robotics for efficient, safe, versatile, and high-quality data collection in the field, and integrate it into your data operations in Cognite Data Fusion. By seamlessly integrating with Cognite Data Fusion, InRobot enriches your digital twin, providing valuable insights for optimizing production and maintenance.InRobot allows for streamlined mission creation, also when you are not in control of the robot, based on previously gathered data, contextualized data in CDF, support for a wide range of sensors (from imagery to acoustic leak detection and various computer vision pipelines). Learn how to do all this in InRobot todayOur comprehensive learning path covers all aspects of InRobot, focusing on key areas such as handling mobile robots and operating workflows for on-site process operators. Through conceptual videos, demonstrations, and hands-on assessments, you
The workflow execution id is 1c3ef35b-c66e-4bdc-bf73-09480e291507.The workflow name is yggdrasil_domain_model_containers_transformations_including_raw_transformations. The tasks threw the following error right after the completion of first step, the error information is : 'reasonForIncompletion': 'Something went wrong. Please report this error to support@cognite.com and provide us with the workflow and task identifiers.', Project: Integral-develop
Hi,We use CDF workflow to process the data present in data model. Based on the inputs, we trigger multiple workflow instances to take the advantage of scalability. We observed that, the workflow execution time is increasing after we trigger more workflow instances. Here is the simple diagram to show how we use workflow: For example:If we run 1 workflow instance to process 20 wellbores (assume some processing logic divided between F1 to F4) with 20 concurrent tasks, the execution time of that workflow instance is 5 mins. Now if we want to process more wellbores say 40, we trigger 2 workflow instances , 1st workflow instance to process 20 wellbores and 2nd workflow instance to process other 20 wellbores and we expect the execution time for all workflows to be approximately same but the total time is increasing if we compare with only 1 workflow instance with 20 tasks. Can you please help me to understand if anything is missing?
Hi everyone, I’m Kimmie McKenzie and I am currently interning with Southern Company Services in Birmingham Alabama. My background is IT. I am a senior at The University of Alabama at Birmingham with a major in Information Systems, a concentration in Cybersecurity, and a minor in Spanish. Throughout my academic and professional career, I have realized that my passion lies in real estate; however, I will continue my degree as well as my internship and simply do the best that I can even though this is not my passion. One of my coworkers expressed their interest in using Cognite and would like for me to present a project of what my department can do with it. I will need all the help I can get!
Hi everyone! My name is Ramalingeswara Reddy, and I'm delighted to join Cognite Hub. I bring with me 17 years of experience as a Project Engineer, primarily working in the Oil and Gas industry. I'm passionate about exploring new technologies and expanding my knowledge in the field.One particular area that has caught my attention is Cognite CDF (Cognite Data Fusion). I'm eager to dive deeper into this powerful platform and discover how it can revolutionize data management and analytics in the industry. I believe that by leveraging Cognite CDF, we can unlock valuable insights and drive significant improvements in operational efficiency.I'm excited to connect with fellow community members, learn from your experiences, and contribute to meaningful discussions. Let's collaborate and explore the potential of Cognite Hub together.
Hello all, I’m Krunal Sakharkar, Front End Software Engineer at SLB based in Pune, India. I’m very excited to learn about Cognite Data Fusion and apply all the knowledge in SLB!!
Hello team, I am bulding an application using the methods in cognite python sdk.I want to create dropdowns for metadata and the values for the same. This similar to the filters on the data explorer screen in the fusion UI:I could not find a direct SDK method to do so.Could you please guide me on how can I achieve that?
A fictitious example, but one that reproduces my problem, is the following code: for event_list in client.events(chunk_size = 500_000, data_set_ids = ids_sites): events = event_list.to_pandas() Error message after just over an hour: CogniteAPIError: Unauthorized | code: 401 | X-Request-ID: 9c8702fc-59bf-9f7a-be47-4876d6b433f3 In fact, if I iterate in another way (for example, filtering by date), I can run code for more than 8 hours (for as long as I want, actually, because I re-authenticate between iterations, preventing the token from expiring). However, I don't want to filter by date because it doesn't provide consistent data volume like iterating by chunks.And apparently, I can't authenticate between iterations in the example I provided here, as it seems the chunk persists the initial authentication, which initially makes sense. Does anyone know how to solve this?
The Assets / Timeseries filter field in Charts shows blank with “recently viewed” list. How to get the full list?Is there any wild card character to show the full list like a * or something ?Also the timeseries filter seems to only work when the filter field has more than 3 characters specified. Is that the expected behaviour?
HiI am practicing through online help manual through “https://learn.cognite.com/” Where I am successfully logged in to “cdf-fundamentals” project. Now want to create new data set as per instruction there is icon on left side to create new data set but I dont find it.Can anyone have idea how to create new data set in “cdf-fundamentals” demo project.
For the Data Scientist Basics: Cognite Charts Hands-on Data quality use case, the time series exist, but do not seem to have any associated data points (TIT202-21, TIT201-20), so I am unable to fully test this use case. Also, for the Valve mileage use case, I believe the time series (VAL_23_ZT_92543:Z.X) data looks different than what the example solution shows (and it doesn’t show up the same way on the PDF document - there is no link for that location on the PDF). Is this correct or did I possibly do something wrong?
Hello Team, I am trying to list views available in my model, using the functionpdmViewList = client.data_modeling.views.list(space= pdmSpace,all_versions=False, limit=-1)This runs successfully in Jupyter notebook when I test it, but fails in Streamlit app, I am unable to figure out the reason. Can someone help if I am missing out on anything here?Below is my code snippet from my app:import streamlit as stimport pandas as pdfrom streamlit.components.v1 import htmlfrom cognite.client import CogniteClientfrom MyLibrary import get_pdm_facetfrom cognite.client.data_classes.filters import ( Equals, And, In, FilterValueList, Or, Prefix)from cognite.client.data_classes.data_modeling import ( NodeApply, # node constructor ViewId, # view reference DirectRelationReference, SingleHopConnectionDefinition, NodeOrEdgeData, NodeId, InstancesDeleteResult)client = CogniteClient()# PDM Model DetailspdmModelExternalId = "production_domain_model"pdmSpace = "slb-pdm-
Hello,Is there a way to use a parameter from OPC-UA Extractor config.yml file in order to make a conversion of some numeric tags (i.e. conversion on the measurement unit from grams to pounds)? As I have not yet found any relatable parameter that would do this and using transformations as the data is pushed in CDF is not efficient on performance as I need to filter out the datapoints already converted.Thanks,Raluca
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